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About
This dashboard shows results from the Berkeley Interpersonal Contact Study (BICS) in Spring 2020.
Caveats / underway:
These results show the national and city samples pooled together
the values presented here have not yet been adjusted to improve sample representativeness
If you have questions or want more information, please contact us at bics@demog.berkeley.edu.
Initial support provided by a Berkeley Population Center pilot grant (NICHD P2CHD073964). If you are interested in funding us, please reach out! This project has been approved by the UC Berkeley IRB (Protocol 2020-03-13128).
Number of interviews by week
Column
Number of conversational contacts
Number of conversational contacts
Number of conversational contacts outside the household
Conversational contacts by age
Conversational contacts outside household by age
Mixing
By age/sex
By age/sex - non-hh contacts
Comparison - all conversational contacts
# A tibble: 16 x 6
# Groups: ego_age [4]
ego_age alter_age bics fb ratio frac_decrease
<chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 [25,35) [25,35) 1.09 7.16 0.152 0.848
2 [25,35) [35,45) 0.5 2.36 0.212 0.788
3 [25,35) [45,65) 0.451 1.25 0.361 0.639
4 [25,35) [65,100] 0.112 0.173 0.646 0.354
5 [35,45) [25,35) 0.513 3.29 0.156 0.844
6 [35,45) [35,45) 1.29 5.87 0.220 0.780
7 [35,45) [45,65) 0.367 1.70 0.215 0.785
8 [35,45) [65,100] 0.202 0.528 0.383 0.617
9 [45,65) [25,35) 0.317 2.23 0.142 0.858
10 [45,65) [35,45) 0.411 3.10 0.132 0.868
11 [45,65) [45,65) 0.943 3.77 0.250 0.750
12 [45,65) [65,100] 0.319 0.755 0.422 0.578
13 [65,100] [25,35) 0.222 0.737 0.301 0.699
14 [65,100] [35,45) 0.322 2.14 0.150 0.850
15 [65,100] [45,65) 0.451 2.00 0.225 0.775
16 [65,100] [65,100] 0.791 2.17 0.364 0.636
Relationships
Relationships, non-household contacts
Locations
Locations - non-household contacts
Contact durations - by relationship
Contact durations - by respondent age
COVID-19
Awareness
Concern
Behavior change
Cities
Number of interviews
Conversational contacts
Conversational contacts outside of household
Model
Overview
To help summarize patterns in the contact survey data, we fit a negative binomial model, accounting for the right-censoring of reported contacts at 10. These models show relationships among people who have completed the survey; have not been adjusted in any way for sampling. We fit these models using the brms package in R.
We modeled the expected log number of reported contacts as a function of age group, city, gender, and household size. The plots below show posterior means and 95% credible intervals for the estimated coefficients. Estimated coefficients greater than 0 imply that the predictor is associated with higher reported numbers of contacts, while estimated coefficients less than 0 imply that the predictor is associated with lower reported numbers of contacts.
There are two models: one for total number of contacts, and one for the number of non-household contacts.
Negative-binomial model for household contacts
Negative-binomial model for non-household contacts
Respondent characteristics
Age/sex
Race/ethnicity
Household size
Contact definition
Respondents to the survey were told to consider someone a contact using this text:
We would like to ask you some questions about people you had in-person conversational contact with yesterday.
By in-person conversational contact, we mean a two-way conversation with three or more words in the physical presence of another person.
You might have conversational contact with family members, friends, co-workers, store clerks, bus drivers, and so forth.
(Please do not count people you contacted exclusively by telephone, text, or online. Only consider people you interacted with face-to-face.)
Data
We plan to produce a version of the data with no identifying information publicly available as soon as we can. If you are a disease modeler who urgently needs to see the microdata, please reach out to us by email.